Application Scheme of Artificial Neural Network in Archives Intelligent Management
Xiaoyun Liu · 2020
For the problems of the current digital archives massive data extraction, such as slow extraction speed and poor quality of data extraction, this paper constructs the archives management model based on BP neural network. Using the value domain characteristics of range type massive data attributes, the scheme divides the distribution samples of digital book and archive data into several sub regions to realize data classification. By constructing neuron model, the error term of output is determined, the weight of each layer of BP neural network is adjusted, and the digital book and archives based on BP neural network is established according to the data output of hidden layer and output layer. The rapid extraction model of quantitative data can realize the rapid extraction of massive data of digital books and archives. The experimental results show that the data extraction speed of the proposed method is faster and the efficiency of data extraction is higher.